distributor-wiki@v2: trajectory LoRA on gemma-4-E4B-it (B5 [ran])

README.md

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+---
+base_model: google/gemma-4-E4B-it
+library_name: peft
+license: apache-2.0
+pipeline_tag: text-generation
+language: [en]
+tags:
+- base_model:adapter:google/gemma-4-E4B-it
+- lora
+- peft
+- gemma
+- knowledge-base
+- tool-use
+- research
+---
+
+# distributor-wiki@v2 — a LoRA that navigates a wiki instead of memorising it
+
+**Research preview from [lora-kernel](https://github.com/EvolvingAgentsLabs/lora-kernel).** This adapter isn't a general
+assistant, and it holds no facts. It learned one habit: walking a library of short markdown pages to
+answer a question. It searches, opens a page, opens the one section it needs, follows the link written
+inside that sentence, sends arithmetic to a calculator, and cites the statement its answer rests on.
+When the library holds nothing on the question, it says `Not in my library.`
+
+The weights hold the navigation and the markdown holds the content. When a fact changes, you edit a
+page and leave the model as it is.
+
+## What it was measured on [ran]
+
+The evaluation world is a generated distributor wiki (`knowledge/distributor-wiki`, seed 20260924). The
+adapter never saw that world in training: its corpus was drawn from 32 *other* generated worlds. An
+answer counts only if the value is right **and** the cited section actually says it.
+
+| arm | W9 headline (2–3 hops, 40) | W9 all (67) | comparison band (40) |
+|---|---|---|---|
+| bare `gemma-4-E4B-it`, same runtime and prompt | 19/40 | — | — |
+| `distributor-wiki@v1` (no comparisons in corpus) | 39/40 | 63/67 | 10/40 |
+| **`distributor-wiki@v2` (this adapter)** | **39/40** | **63/67** | **37/40** (28 : 1 paired vs v1, p = 1.1e-7) |
+
+Runs: `results/M7-W9-atomic-statements-20260924`, B1, and `results/B5-comparison-corpus-20260926` in the
+repository. The release manifest is `releases/distributor-wiki@v2.json`, and the adapter sha256 is
+`d4d91ea4aa7a8ffcd82beabb87d07112c02b212388412fb61f43df49d3eb93d6`.
+
+## Limits, stated plainly
+
+- **Every world it has seen or been scored on is generated by one generator.** It hasn't been measured
+  on a hand-written or real organisation's library. A model trained on generated data can learn the
+  generator's quirks, and this one hasn't been tested outside them.
+- **It expects this page format**: YAML front matter (`id`, `when`, `what`) followed by one `§anchor`
+  statement per line, with links as `[[page-id]]` inside the statements. See `knowledge/distributor-wiki/`.
+- **It needs the runtime.** The model writes `<search>`, `<open>` and `<calc>` tags. The runtime stops at
+  each closing tag, writes the result inline after `= `, and lets generation continue. This is not
+  OpenAI `tool_calls`: one adapter in this project scored 11/90 served that way and 90/90 served inline
+  as it was trained.
+- Thinking is **off** (`enable_thinking=false`) in every render. The vision and audio towers are excluded
+  from the LoRA.
+
+## How to run it
+
+The runtime lives in `memory/` (`Library`, `Conversation`). The runner that produced the numbers above
+is `training/wiki/wiki_arm.py`, served through vLLM with LoRA enabled. To reproduce a score, see
+`docs/SERVING.md` and `docs/MEMORY.md` §1.6 in the repository.
+
+Recipe: r 16, alpha 32, 3 epochs, lr 2e-4, effective batch 16, max_seq 1536, all attention and MLP
+projections, seed 1. The corpus is `training/wiki/data/train_cmp.jsonl` (728 walks, sha256 `7b307d53…`).
+
+Apache-2.0, like the base model.

adapter_config.json

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+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": null,
+  "base_model_name_or_path": "google/gemma-4-E4B-it",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": ".*(vision_tower|audio_tower|multi_modal_projector|embed_vision|embed_audio).*",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "lora_ga_config": null,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "monteclora_config": null,
+  "peft_type": "LORA",
+  "peft_version": "0.20.0",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "up_proj",
+    "down_proj",
+    "gate_proj",
+    "q_proj",
+    "o_proj",
+    "v_proj",
+    "k_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_bdlora": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false,
+  "velora_config": null
+}

adapter_model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:d4d91ea4aa7a8ffcd82beabb87d07112c02b212388412fb61f43df49d3eb93d6
+size 139602776